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The Safe Software Blog
USER
Author:
Erin Lemky
About Our Customers    |    September 23, 2016    |    By Erin Lemky

Iowa DOT: Preparing Data for APIs

GIS undergrad David Runneals has come a long way since his internship. Now he’s building APIs to make Iowa DOT’s public data more accessible, opening it to innovative applications. To populate the data, he once again chose FME to do the heavy lifting.

FME
Author:
Mark Ireland
About FME    |    September 21, 2016    |    By Mark Ireland

FME 2016.1 Use Case: HTML Reports of Vancouver Public Art

Hi FME’ers, I’d promised to post a couple of examples of creating HTML reports with FME, and here is one of them. Here I was creating a Point-in-Polygon example as part of our FME for GIS Tutorial. Because there can be more than one point in a polygon, part of the article needed to discuss […]

DATA
Author:
Tiana Warner
About Data    |    September 19, 2016    |    By Tiana Warner

R, Matey! Adding Statistical Power to FME Workflows

Shiver me timbers! Today be Talk Like A Pirate Day, and our crew be celebratin’ by sharing secrets of FME’s support for RRRRR! This here be the motherload of all statistical analysis, and if ye know the code ye can keelhaul the StatisticsCalculator— WAIT STOP DON’T LEAVE. I won’t spend the whole blog in a […]

FME
Author:
Fil Vera
Author:
Tiana Warner
About FME    |    August 29, 2016    |    By Fil Vera and Tiana Warner

Technical Interview Advice, Secrets, and Survival Tips

What do tech companies like Safe Software look for in potential employees? Our recruiters share advice on the interview process, with tips on how to tackle those notorious problem-solving questions. Most tech companies have a multi-step interview process that includes a phone screen, a face-to-face interview, and a hands-on technical interview. The phone screen is usually casual […]

DATA
Author:
Tiana Warner
About Data    |    August 24, 2016    |    By Tiana Warner

6 Tableau Tasks You Didn’t Know You Could Do

We all know business intelligence is important — but getting started with advanced analytics is daunting. That’s probably why everyone from the US Department of the Interior to The Texas Rangers has turned to Tableau for help. Yes, it’s possible to turn something as scary as “segmentation and cohort analysis” into a visual dashboard that a […]

DATA
Author:
Roger Aikema
About Data    |    August 22, 2016    |    By Roger Aikema

Importing Spatial Data into Tableau using FME

Today we welcome guest bloggers Régis Longchamp and David Reksten, FME Certified Professionals from INSER. They will share part of an example they created for a client, which uses Tableau and FME to create a cartographic representation of the population distribution in Switzerland. INSER is a GIS consulting company based in Lausanne, Swizerland, and has been a Safe Software Gold […]

FME
Author:
Dmitri Bagh
About FME    |    August 18, 2016    |    By Dmitri Bagh

#FMECoin Contest in Review

My regular morning begins with a cup of coffee, news websites, Facebook (just kidding – I am among 541 people in North America who don’t have a Facebook account), and since April, with checking the new FME coin submissions. In four months, there were only seven days when we didn’t receive any new coin tweets. […]

FME
Author:
Don Murray
About Data About FME    |    August 3, 2016    |    By Don Murray

FME Server on Mac using ‘Docker for Mac’ (Part 2 of Docker at Safe)

The first announcement of Docker for Mac was both unexpected and very exciting as it promised to enabled Docker containers to run “natively” on the Mac. I have “natively” in quotation marks as containers are not really run native but the whizzes at Docker pulled off some amazing magic to create a native container feel thus making the Mac a great Docker host. Instead of using VirtualBox or another heavy virtual machine, Docker for Mac uses the lightweight xhyve virtualization technology to host the Linux version of FME Server.

DATA
Author:
Tiana Warner
About Data    |    July 13, 2016    |    By Tiana Warner

Understanding XML: The Human’s Guide to Machine-Readable Data

Data formats are designed to be either machine readable (structured so computers can process it) or human readable (easy for humans to understand). Some formats, like XML and JSON, are allegedly both. Let’s call these ambivert formats. This means when you, a human, open the file, you can read what’s inside — but the data […]